Solutions for Healthcare

Better Data for Better Patient Care and Increased Revenue

Solutions for Quality Patient Data

Our solutions keep patient and clinical data clean and accurate to help you improve healthcare operations, better understand your patients, make new discoveries, and lower costs.

PATIENT ONBOARDING

Validate, correct and standardize patient contact data at point-of-entry – name, address, email and phone – to improve onboarding and minimize risk. Autocomplete addresses as you type.

REMOVE DUPLICATE RECORDS

Match, merge and purge duplicate patient records across households, facilities and time to minimize patient frustration, billing and claim errors, and legal liabilities.


ENSURE TIMELY PAYMENTS

Update the addresses of your customers as they move to ensure invoices arrive in a timely manner and claims are submitted with accurate patient information to avoid denials.




UNDERSTAND SERVICE TERRITORIES

Add location intelligence like exact drive time and true distance between your patients or new subscribers and your facilities. Get geographic info for a better understanding of the areas you service.

IMPROVE HEALTH INITIATIVES

Add precise demographic data to your records like age, sex, race and income to help ensure better resource allocation, patient care and public policy.



AI-ENABLED SEMANTIC TECHNOLOGY

Check, verify, append and autocomplete pharmaceutical names, variants, dosages and spellings. Clean, connect and harmonize multiple datasets to create one unified resource. Enable clinical insight and discovery with machine reasoning.

Image layer

Minimized labor costs

Arrow

Fully-automated
contact data cleansing

Arrow

Now catches
errors in real time

Arrow

Easily integrated into
existing .NET and SQL processes

Arrow

Used GeoCoder to
find nearby physicians in network

Arrow
  • Chris Lloyd
    Director of Database Services

    "GeoCoder allows us to maintain multiple addresses for the same physician even when we are receiving and loading the data from more than one source. We use the mileage distance between addresses to write proprietary business rules to locate physicians that practice in multiple locations, and even across state borders."

Case Study: CalOptima

Find out how CalOptima, the second largest health insurer in Orange County, migrated 422,000 members, 5,800 physicians, and 24 hospitals into one data warehouse with the help of Melissa’s Data Quality Components for SSIS.


View CalOptima Case Study
Image layer

Easy implementation
with SSIS

Arrow

Used GeoCoder to find
nearby physicians in network

Arrow

Better knowledge
of member locations

Arrow

Reduced returned
mail costs

Arrow
  • Osvaldo Cruz
    Data Warehouse Architect

    "Our main objective was to add value to the data produced for business users. Having conformed and integrated data is valuable, but the added value of recognizing valid addresses is significant. One of the cost-driven indicators is returned mail and missing communication with members."